U.S. patent application number 16/548788 was filed with the patent office on 2020-02-27 for low power circuitry for biasing a multi-channel gas sensor array and to act as a transducer for a digital back-end.
The applicant listed for this patent is AerNos, Inc.. Invention is credited to Albert CHEN, Sundip R. DOSHI.
Application Number | 20200064321 16/548788 |
Document ID | / |
Family ID | 69586085 |
Filed Date | 2020-02-27 |
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United States Patent
Application |
20200064321 |
Kind Code |
A1 |
CHEN; Albert ; et
al. |
February 27, 2020 |
LOW POWER CIRCUITRY FOR BIASING A MULTI-CHANNEL GAS SENSOR ARRAY
AND TO ACT AS A TRANSDUCER FOR A DIGITAL BACK-END
Abstract
A nanomaterial-based gas sensor system comprising a low voltage
circuitry which includes a transducer to detect changes in
electrical properties of a multi-channel gas sensor array, analog
signal conditioning, and an A/D conversion to provide a signal to a
digital back-end.
Inventors: |
CHEN; Albert; (Poway,
CA) ; DOSHI; Sundip R.; (San Diego, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
AerNos, Inc. |
San Diego |
CA |
US |
|
|
Family ID: |
69586085 |
Appl. No.: |
16/548788 |
Filed: |
August 22, 2019 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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62721289 |
Aug 22, 2018 |
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62721293 |
Aug 22, 2018 |
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62721296 |
Aug 22, 2018 |
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62721302 |
Aug 22, 2018 |
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62721306 |
Aug 22, 2018 |
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62721309 |
Aug 22, 2018 |
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62721311 |
Aug 22, 2018 |
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62799466 |
Jan 31, 2019 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B01J 31/1691 20130101;
G01N 33/0022 20130101; G05B 2219/25127 20130101; B01J 21/185
20130101; G01N 27/125 20130101; B82Y 40/00 20130101; G01N 27/127
20130101; G01N 33/0011 20130101; G01N 27/046 20130101; G01N 27/128
20130101; G05B 19/042 20130101; G01N 27/226 20130101; B01J 23/00
20130101; G01N 33/0047 20130101; G01N 27/122 20130101; G01N 27/228
20130101; G01N 33/0042 20130101; G01N 33/004 20130101; G01N 33/0037
20130101; G01N 27/4075 20130101; G01N 33/0031 20130101; G01N 27/227
20130101; G05B 2219/25257 20130101; B82Y 30/00 20130101; G01N
27/121 20130101 |
International
Class: |
G01N 33/00 20060101
G01N033/00 |
Claims
1. A sensor system comprising: a sensor array comprising a
plurality of sensing elements, wherein each of the plurality of
sensing elements are functionalized with a deposited mixture
consisting of hybrid nanostructures and a molecular formulation
specifically targeting at least one of a plurality of gases, and
wherein each of the plurality of sensing elements comprises a
resistance and a capacitance, and wherein at least one resistance
and capacitance are altered when the interacting with gaseous
chemical compounds; an analog front-end coupled with the sensor
array and configured to detect the alteration in the resistance or
capacitance and produce an analog signal indicative thereof, power
each of a plurality of sensing channels associated with the
plurality of sensing elements, and convert the analog signal to a
digital signal, the analog-front end comprising: an
Analog-to-Digital (ADC), a parking circuit, and a measurement
circuit; and a digital back end coupled with the analog-front end
and configured to control the analog front-end, the digital backend
comprising: memory comprising, algorithms, models and
instructions.
2. The system of claim 1, wherein the instructions are configured
to cause the processor to dynamically optimizes the analog signal
by: calculating, storing, and setting the gain for each of a
plurality of sensor channel, wherein each channel is associated
with a sensing element, prior to conversion by the ADC, and
increasing the signal-to-noise ratio through various oversampling
factors.
3. The system of claim 1, wherein the analog-front end is further
configured to do at least one of the following: minimize
self-heating effects for each of the plurality of sensing elements;
maintain operation of each of the plurality of sensing elements in
a linear region; minimize power consumption for each of the
plurality of sensing element; and prevent short-circuits for each
of the plurality of sensing elements.
4. The system of claim 1, wherein the analog-front end is further
configured to apply constant voltage across a nanomaterial-based
sensor.
5. The system of claim 1 wherein the parking circuit is configured
to provide a constant voltage to any number of connected sensing
channels simultaneously, limit current through each individual
sensor channel, and.
6. The system of claim 5, wherein the parking circuit comprises a
plurality of switches, and wherein the parking circuit is
configured to connect or disconnect any individual sensing channel
via the plurality of switches.
7. The system of claim 5, wherein the constant voltage is about
1V.
8. The system of claim 5, wherein the current is limited to about 1
mA
9. The system of claim 1, wherein the measurement circuit is
configured to provide a constant voltage to at least some of the
plurality of sensing channels simultaneously and limit the total
current through each of the plurality of sensing channels.
10. The system of claim 9, wherein the constant voltage is about
1V.
11. The system of claim 9, wherein the current is limited to about
1 mA.
12. The system of claim 9, wherein the measurement circuit
comprises either a plurality of switches or a multiplexer
configured to connect or disconnect any of the plurality of sensing
channels and to minimize settling time to the circuit when
switching channels; add an offset to an overall signal associated
with sensing channels of the plurality of sensing channels to
generate a larger amplitude that is less prone to noise, and closer
to the reference; add signals from multiple sensing channels of the
plurality of sensing channels to generate a signal of larger
amplitude that is easier to measure; and add the signals from
multiple sensing channels of the plurality of sensing channels to
combine the sensing characteristics in a single measurement.
13. The measurement circuit of claim 1, further configured to
isolate the sensing channels of the plurality of sensing channels
that are being measured from a gain stage, and a data acquisition
stage as well as from the sensing channels of the plurality of
sensing channels connected to the parking circuit.
14. The measurement circuit of claim 1, further comprising one or
more gain stages, wherein each of the one or more gain stages
comprise: a current mirror, wherein gain is implemented in the
current mirror with various mirroring ratios; a transimpedance
amplifier, configured to converting the current into a voltage; a
set of selectable resistances for converting the current into a
voltage, applying gain to the conversion of current to voltage; and
a secondary gain stage, comprising an OPAMP.
15. The system of claim 14, wherein a spacing of selectable gain
settings is pre-selected and optimized for the range of each of the
plurality of sensing element.
16. The system of claim 15, wherein the spacing of selectable gain
settings is geometrically spaced.
17. The system of claim 1, further comprising a make before break
circuit, configured to minimize a transient load on a sensing
element when the sensing element is being switched from the parking
circuit to the measurement circuit and vice versa.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority to U.S. Provisional Patent
Application No. 62/721,289, filed Aug. 22, 2018, U.S. Provisional
Patent Application No. 62/721,293, filed Aug. 22, 2018, U.S.
Provisional Patent Application No. 62/721,296, filed Aug. 22, 2018,
U.S. Provisional Application No. 62/721,302, filed Aug. 22, 2018,
U.S. Provisional Patent Application No. 62/721,306, filed Aug. 22,
2018, U.S. Provisional Patent Application No. 62/721,309, filed
Aug. 22, 2018, U.S. Provisional Application No. 62/721,311, filed
Aug. 22, 2018, U.S. Provisional Patent Application No. 62/799,466,
filed Jan. 31, 2019, the contents of which are incorporated herein
by reference.
BACKGROUND
1. Technical Field
[0002] The embodiments herein relate to a nano gas sensing system,
and more particularly to an analog front-end for biasing and
measuring of one or more gas sensors and conditioning and
conversion of an analog signal(s) for an array of
nanomaterial-based gas sensors for a digital back-end.
2. Related Art
[0003] Conventional digital gas sensor systems typically power and
measure a single metal oxide sensor. Digital gas sensors are
typically static in their sampling methodology, and in general,
this involves sampling an ADC for converting the voltage to a
digital value, at fixed intervals. This value is then converted
back to a gas concentration, typically via a linear fit model.
[0004] Conventional techniques for measuring a gas sensor typically
provide either a voltage or current source which may or may not be
constant. The quantity being measured is turned into a voltage for
conversion into a digital signal. In many applications there is a
limited range of measurement, or a tradeoff between measurement
range and accuracy. Other techniques that rely on an optical method
of measurement and detection are often bulky and/or expensive.
[0005] In applications with multiple sensors, the measurement
circuitry is duplicated and/or multiplexed. As the number of
sensors increases, the delay between each sensor's measurement may
lead to difficulty in capturing the true signal of interest.
[0006] Commercially available gas sensors can also be cumbersome to
use, expensive and limited in performance (e.g. accuracy,
selectivity, lowest detection limit, etc.). In addition, other
major drawbacks may include inability to detect different types of
gases at the same time, inability to measure absolute concentration
of individual gases, the requirement for frequent re-calibration, a
size incompatible with integration into small form factor systems
such as wearable devices, the reliance on power-hungry techniques
such as heating or on technologies not well suited to manufacturing
in very high volume.
[0007] The ability to accurately detect multiple gases at the same
time, often at parts-per-billion (PPB) sensitivity is becoming
crucial to a growing number of industries as well as to the
world-wide expansion of air quality monitoring initiatives aiming
to address household and urban air pollution challenges.
SUMMARY
[0008] A nano gas sensor architecture that delivers key fundamental
attributes required for the broad deployment of sensors capable of
low detection limits (PPB) in support of highly granular collection
of gas information in ambient air is described herein.
[0009] According to one aspect, a sensor system comprises a sensor
array comprising a plurality of sensing elements, wherein each of
the plurality of sensing elements are functionalized with a
deposited mixture consisting of hybrid nanostructures and a
molecular formulation specifically targeting at least one of a
plurality of gases, and wherein each of the plurality of sensing
elements comprises a resistance and a capacitance, and wherein at
least one resistance and capacitance are altered when the
interacting with gaseous chemical compounds; an analog front-end
coupled with the sensor array and configured to detect the
alteration in the resistance or capacitance and produce an analog
signal indicative thereof, power each of a plurality of sensing
channels associated with each the plurality of sensing elements,
and convert the analog signal to a digital signal, the analog-front
end comprising: an Analog-to-Digital (ADC), a parking circuit, and
a measurement circuit; and a digital back end coupled with the
analog-front end and configured to control the analog front-end,
the digital backend comprising: memory comprising, algorithms,
models and instructions.
[0010] These and other features, aspects, and embodiments are
described below in the section entitled "Detailed Description."
BRIEF DESCRIPTION OF DRAWINGS
[0011] Features, aspects, and embodiments are described in
conjunction with the attached drawings, in which:
[0012] FIG. 1 illustrates the basic principles to construct a gas
sensor;
[0013] FIG. 2 is a prospective view of a physical implementation of
a hybrid nanostructure gas sensing element in accordance with one
embodiment;
[0014] FIG. 3 is a diagram illustrating an embodiment of a gas
sensor array;
[0015] FIG. 4 is a block diagram of the hybrid nanostructure gas
sensor system that incorporates the hybrid nanostructure gas
sensing array of FIG. 3 in accordance with one embodiment;
[0016] FIG. 5 is a chart showing the flow of gas information
through the hybrid nanostructure gas sensor system of FIG. 4;
[0017] FIG. 6 is an exploded view of an example wearable product
built around a PCB embodiment of the hybrid nanostructure gas
sensor system of FIG. 4;
[0018] FIG. 7 is a block diagram illustrating an example wired or
wireless system that can be used in connection with various
embodiments described herein;
[0019] FIG. 8 is a diagram illustrating an example, single channel
that can be replicated in the sensor array of FIG. 3 included in
the sensor chip of FIGS. 3 and 4 in accordance with one
embodiment;
[0020] FIGS. 9 and 10 are diagrams illustrating example embodiments
for a complete sensor chip of FIG. 3 comprising 32 channels;
[0021] FIGS. 11 and 12 are diagrams illustrating another example
embodiment for a complete sensor chip comprising 20 channels;
[0022] FIG. 13 is an illustration of a complete wafer implementing
either embodiment described in FIGS. 5 through 7;
[0023] FIG. 14 is a diagram illustrating a parking circuit that can
be included in the system of FIG. 4 in accordance with one example
embodiment;
[0024] FIG. 15 is a diagram illustrating an example measurement
circuit that can be included in the system of FIG. 4 in accordance
with one embodiment;
[0025] FIG. 16 is a diagram of an example multiplexer
implementation that can be included in the circuit of FIG. 15 in
accordance with one embodiment;
[0026] FIG. 17 is a diagram illustrating an example parking circuit
and example measurement circuit coupled with a plurality of
sensors;
[0027] FIG. 18 is a diagram illustrating an OP-AMP circuit that can
be used in place of the current mirror of FIG. 15;
[0028] FIG. 19 is a diagram illustrating a circuit for converting
the output of the current mirror of the measurement circuit of FIG.
15 into an analog signal that can be sent to the ADC included in
the system of FIG. 4;
[0029] FIG. 20 is a diagram illustrating certain components of the
digital backend of the system of FIG. 4 in accordance with one
embodiment;
[0030] FIG. 21 is a graph illustrating and an example plot of
dynamic oversampling rate that can be implemented in the digital
backend system of FIG. 4 in accordance with one embodiment;
[0031] FIG. 22 is a graph illustrating and an example plot of
optimized vs non-optimized settling time that can be implemented in
the digital backend system of FIG. 4 in accordance with one
embodiment; and
[0032] FIG. 23 is a graph illustrating and an example plot of
dynamic sampling rate over signal, and duty cycle that can be
implemented in the digital backend system of FIG. 4 in accordance
with one embodiment.
DETAILED DESCRIPTION
[0033] Embodiments for a hybrid nanostructure gas sensing system
are described herein. The disclosure and the various features and
advantageous details thereof are explained more fully with
reference to the non-limiting embodiments and examples that are
described and/or illustrated in the accompanying drawings and
detailed in the following. It should be noted that the features
illustrated in the drawings are not necessarily drawn to scale, and
features of one embodiment may be employed with other embodiments
as the skilled artisan would recognize, even if not explicitly
stated herein. Descriptions of well-known components and processing
techniques may be omitted so as to not unnecessarily obscure the
embodiments of the disclosure. The examples used herein are
intended merely to facilitate an understanding of ways in which the
disclosure may be practiced and to further enable those of skill in
the art to practice the embodiments of the disclosure. Accordingly,
the examples and embodiments herein should not be construed as
limiting the scope of the disclosure. Moreover, it is noted that
like reference numerals represent similar parts throughout the
several views of the drawings.
[0034] The architecture embodied in the hybrid nanostructure gas
sensing system described herein achieves the basic requirement of
selectively identifying the presence of a gas analyte in diverse
mixtures of ambient air but it is also designed to identify
multiple gases at the same time, to be compatible in terms of size
and power with very small form factors (including for mobile and
wearable applications), to be easy to Integrate in IoT applications
and to be self-calibrating, thus unshakling the application and/or
the service provider from the burden and expense of regular
re-calibration.
[0035] FIG. 1 describes the basic ingredients for a successful gas
sensor 100. As can be seen, such a sensor includes a sensing
element 102 that is created by depositing a sensitive layer 104
over a substrate 106. The sensing element 102 can then interact
with gaseous chemical compounds 108 altering one or more electrical
properties of the sensing element 102. The change in electrical
properties can be detected by feeding the sensor raw signals 110
through specially designed signal processing electronics 112. The
resulting response signals 114 can be measured and quantified
directly or through the application of pattern recognition
techniques.
[0036] The embodiments described herein comprise six basic
elements. The first is the basic sensor element or sensing channel,
which combines a structural component, built on a substrate
suitable for reliable high-volume manufacturing, with a deposited
electrolyte containing hybrid nano structures in suspension. The
formulation of the electrolyte is specific to a particular gas or
family of gases. A silicon substrate 106 and the structural
component can be built using a MEMS manufacturing process. The
structural component is essentially an unfinished electrical
circuit between two electrodes. The deposition of the electrolyte
completes the electrical circuit and, when biased and exposed to
gas analytes, changes to one or more of the electrical
characteristics of the circuit are used to detect and measure
gases.
[0037] The second element is the arrangement of multiple sensing
channels into an array structure specifically designed and
optimized to interface with data acquisition electronics 112. The
array structure, combined with the use of pattern recognition
algorithms, makes it possible to detect multiple gases at the same
time with a single sensor by customizing one or more of the
individual sensing channels in the array for a specific gas or
family of gases while using other sensing channels to facilitate
such critical functions as selectivity.
[0038] FIG. 2 is a conceptual view of a hybrid nanostructure
physical sensing element 102 in accordance with one example
embodiment. Different materials can be used for the substrate 106
on which the rest of the sensing element 102 is constructed. But
from the perspective of very high volume manufacturing, silicon
technology can be preferred and specifically MEMS technology, which
provides the necessary foundation for a customer-defined set of
manufacturing steps with the flexibility to modulate the complexity
of the process based on the sophistication of the sensor chip being
built, e.g., to support further innovation or to address special
product needs. Silicon technology also provides access to
time-proven test methods and multiple sources of Automated Test
Equipment that can be customized to fit the needs of gas sensing
technology.
[0039] The sensing element 102 is made of an incomplete or "open"
electrical circuit between two electrodes 202, which is then
completed or "closed" by depositing, a molecular formulation
electrolyte 204 with hybrid nanostructures 208 in suspension. The
process is compatible with several commonly used deposition
techniques but does require specially customized equipment and
proprietary techniques to achieve the desired quality and
reproducibility in a high-volume manufacturing environment. In
certain embodiments, the sensing element 102 can be specially
patterned to support efficient deposition of nanomaterial in
pico-litter amounts and to facilitate incorporation of multiple
elements into an array to enables the design of multi-gas
sensors.
[0040] Electrodes 202 can then be bonded to bonding pads 206 in
order to communicate signals 110 to the rest of the system.
[0041] One or more molecular formulations may be necessary to
completely and selectively identify a particular gas. Combining
multiple sensing elements 102, each capable of being "programmed"
with a unique formulation, into a sensor array provides the
flexibility necessary to detect and measure multiple gases at the
same time. It also enables rich functional options such as for
instance measuring humidity, an important factor to be accounted
for in any gas sensor design, directly on the sensor chip (after
all water vapor is just another gas). Another example is the
combination for the same gas or family of gases of a formulation
capable of very fast reaction to the presence of the gas while
another formulation, slower acting, may be used for accurate
concentration measurement; this would be important in applications
where a very fast warning to the presence of a dangerous substance
is required but actual accurate concentration measurement may not
be needed at the same time (e.g. first responders in an industrial
emergency situation).
[0042] FIG. 3 illustrates the preferred embodiment of a
multichannel, gas sensor array 305 where a silicon substrate 302 is
used with a MEMS manufacturing process to build the structure of
the sensing channels on which the molecular formulations 204 can be
deposited. For illustration purposes the size of the individual
sensor die 304 is shown as being much larger than achievable in
practice; a single 8'' wafer 300 will typically yield several
thousand multi-gas capable sensor chips. An array 305 of sensing
elements 102 is implemented on a single die 304 and each wafer 300
yields several thousand dies or chips 304. Each sensing element 102
can then be functionalized by depositing a specific molecular
formulation 204 thereon.
[0043] Thus, after MEMS manufacturing, additional steps are
required to complete the fabrication of each sensing element 102.
First, molecular formulations 204 are deposited and cured using
specialized equipment. This happens at wafer level and the
equipment is designed in a modular fashion to allow for the scaling
of the output of a manufacturing facility by duplicating modules
and fabrication processes in a copy-exactly fashion. After
completion of the manufacturing steps, the wafers 300 must be
singulated using a clean dicing technology in order to prevent
damage to the sensing elements 102. An example of such technology
is Stealth dicing.
[0044] A channel 102 consists of two main elements: electrodes and
a well. The electrodes, over which the formulation 204 is being
deposited, form an open circuit until hybrid nanomaterial 208
creates a bridge between two adjacent electrodes. The well is a
wall surrounding the electrodes. The well prevents the overflow of
material during the formulation deposition process. The well is
formed in two sections ("top" and "bottom"). A complete channel 102
therefore consists of a fixed number of electrode segments and two
separate walls outside the top and bottom electrodes. Assuming a
chip has 32 channels, a total of 3,300 chips form a complete 8-inch
wafer.
[0045] FIG. 8 is diagram illustrating an example, single channel
102 in accordance with one embodiment. Each channel 102 consists of
electrodes 802 and well 804. The electrodes 802 are on top of a
Si/SiO.sub.2 substrate 302 (not shown in FIG. 8). In certain
embodiments the material of the substrate 302 is made of Silicon
(Si), but the choice of substrate is not limited to Si. Other
materials such as glass, aluminum oxide, a polyimide soft film, a
printed circuit board (PCB), and a variety of paper supports can be
chosen depending on the embodiment. A dielectric layer (not shown)
included in the substrate can be made of Silicon Dioxide
(SiO.sub.2), but again the selection of material is not limited to
SiO.sub.2; For example, another option could be Silicon Nitride
(Si.sub.3N.sub.4).
[0046] In certain embodiment, the thickness of the dielectric
SiO.sub.2 layer is 300 nm, but it can range from about 200 to 500
nm, including the following specific values: 200, 220, 230, 240,
250, 300, 350, 400, 450, and 500 nm. The thickness of the substrate
302, can be 500 .mu.m but could range from about 250 to 750 .mu.m,
including the following specific values: 250, 300, 350, 400, 450,
500, 550, 600, 650, 700, and 750 .mu.m. The width of a single
channel 102 can be 200 .mu.m but could range from about 100 to 600
.mu.m, including the following specific values: 100, 150, 200, 250,
300, 350, 400, 450, 500, 550, and 600 .mu.m.
[0047] In certain embodiments, the electrode 802 is built using
Platinum (Pt) and Titanium (Ti) layers but the choice of material
can include other metals such as Chromium (Cr) and Gold (Au). In
certain embodiments, the total thickness of the Pt/Ti layer is 300
nm but could range from about 200 to 400 nm, including the
following specific values: 200, 250, 300, 350, 400 nm. In certain
embodiments, the shape of the electrode 802 is circular as shown.
This specific shape was chosen for the following reasons: 1) create
a homogeneous deposition form, 2) keep the material formulation
within the electrodes for optimum sensor performance, 3) prevent
the overflow of the deposited formulation, and 4) ensure fast
drying of the deposited formulation; however, it will be understood
that other shapes can be used in conjunction with the embodiments
described herein.
[0048] In certain embodiments, the width of the electrode is 5
.mu.m but could range from 3 to 10 .mu.m, including the following
specific values: 3, 4, 5, 6, 7, 8, 9, and 10 .mu.m. In certain
embodiments, the number of coils per electrode pair is 7 but could
range from 7 to 14.
[0049] In certain embodiments, the well 804 has top and bottom
sections with the two sections combining to create the full well
804 around the electrodes 802. The material for the well can be
Si.sub.3N.sub.4 but other materials could also be used (e.g. a
combination of SiO.sub.2 and Si.sub.3N.sub.4). In certain
embodiments, the well 804 is designed to 1) confine the formulation
over the electrodes 802, 2) prevent cross-contaminations from an
adjacent channel, and 3) provide an alignment key for volume
deposition equipment.
[0050] The gap 806 between the electrodes 802 is where the sensing
formulation 204 needs to be deposited. The deposited formulation
204 creates the connection necessary to complete the electrical
circuit and ultimately becomes a sensitive layer for gas analytes
in various applications. The circuit is open if a formulation 204
has not been deposited. In certain embodiments, the size of the gap
is 3 .mu.m, but the gap size could range from about 2.5 to 10
.mu.m, including the following specific values: 2.5, 3, 3.5, 4,
4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5 and 10 .mu.m.
[0051] FIGS. 9 and 10 are diagrams illustrating example embodiments
for a complete sensor chip 304 comprising 32 channels. In certain
embodiments, each chip 304 is 2.7 mm.times.2.7 mm and has four,
separate common ground 902 for reducing signal noise and to create
redundancy to reduce the chance of chip malfunction. Alignment key
1 (904) is used for alignment during wafer dicing (die
singulation). Alignment key 2 (906) is a special mark for precise
alignment within the wafer for high volume manufacturing. By
combining both alignment keys 1 and 2, very precise volume
deposition can be achieved.
[0052] In certain embodiments, each chip 304 has 32 bonding pads
908 for wire bonding individual channels 102 to connect the on-chip
circuitry to off-chip electronics. Every channel 102 can be an
individual sensor for gas sensing purpose. As illustrated in FIG.
10, in certain embodiments, each pad 908 is 0.1 mm.times.0.1 mm and
the spacing between two bonding pads 908 is 0.075 mm. Moreover, as
illustrated, the overall chip 304 area can be about 2.7
mm.times.2.7 mm, and the diameter of each channel 102 can be
approximately 0.225 mm. Still moreover, while the example of FIGS.
9 and 10 show a chip 305 with 32 channels, a variety of
implementations are possible with 8, 16, 20, 24, 32, 36 or 40
channels, yielding a variety of chip area from 2 mm.times.2 mm to 5
mm.times.5 mm.
[0053] The number of deposited formulations 204 can vary depending
on the target application. In certain embodiments with 32 channels,
as many as 32 different formulations 204 could be deposited;
however, it could be any number between 1 and 32. The spacing
between each channel 102, from center to center, can be adjusted to
fit various requirements and applications. In certain embodiments,
the spacing is 600 .mu.m but could range from 400 to 800 .mu.m.
[0054] FIGS. 11 and 12 are diagrams illustrating another example
embodiment for a complete sensor chip 304 comprising 20 channels
102. To adapt to a variety of applications, different numbers of
channels 102 can be used. In this particular embodiment, each
channel 102 is larger (400 .mu.m) than in the 32-channel embodiment
described in FIGS. 9 and 10. For certain applications, such as air
quality monitoring or leak detection, to achieve the goal and
retrieve useful information, the volume of deposited sensitive
material 204 in each channel 102 may need to be more than a
nano-liter. Moreover, in certain specific applications such as
in-home environment monitoring, a larger channel size is critical
to obtain a clean signal for precise measurement.
[0055] In embodiment of FIGS. 11 and 12, the chip 304 is 3
mm.times.3 mm in area. Each chip 304 has 20 individual bonding pads
1108 for signal read-out. Each pad is 0.1 mm.times.0.1 mm and the
spacing between two bonding pads 1108 is 0.1 mm and 0.37 mm
respectively, depending on the location of the pads 1108. Alignment
keys 1 (1104) and 2 (1106) serve the same chip alignment purpose
and provide the means for precise volume deposition.
[0056] FIG. 13 is an illustration of a complete wafer 300
implementing either embodiment described in FIGS. 9 through 11.
With a chip area of 3 mm.times.3 mm, an 8-inch wafer consists of
approximately 3,300 chips. The spacing between each chip 304 is set
for optimum dicing operation. The amount of chips 304 per wafer 300
has also been calculated to support high wafer processing
yield.
[0057] The third element is the electronic transducer that detects
changes in the electrical characteristics of the sensor array 305,
provides signal conditioning and converts the analog signal from
the sensor elements 102 into a digital form usable by the data
acquisition system, described in more detail below. The transducer
can be a low voltage analog circuit that provides biasing to the
array of sensing channels 102 and two functional modes: parking and
measurement. Sensing channels 102 are in parking mode either when
not in measurement mode or when not used/enabled at all for a given
application. The circuitry is designed to maintain the sensing
channels 102 in a linear region of operation, to optimize power
consumption, to enable any combination of channels 102 in either
parking or measurement modes and to provide a seamless transition
between modes.
[0058] FIGS. 14-19 illustrates low power circuitry for biasing a
multi-channel gas sensor array 305. The circuitry described
consists of two main blocks. The first block where the sensors 102
are not being measured, is referred to as the "parking circuit".
The other is used when the sensors 102 are being measured and is
referred to as the "measurement circuit". The electrical
characteristics of interest are both the static resistance and the
differential resistance. A sensing element 102 in this case refers
to the portion of a sensor 102, which has been functionalized by
nanomaterials 208. The sensor channel is the sensing element 102,
the substrate, and other hardware providing the connection between
the sensing element 102 to the board.
[0059] FIG. 14 is a diagram illustrating a parking circuit 1400 in
accordance with one example embodiment. The parking circuit 1400
allows for the connection of N sensors 102 for conditioning while
waiting to be measured. The parking circuit 1400 consists of a
constant voltage source 1402, an OP AMP 1404 and Single Pole Single
Throw switches (SPST) 1406 to connect/disconnect each sensor 102
independently.
[0060] The voltage reference 1402 can be a precision 1V reference
conditioned using a buffer amplifier. The reference voltage can be
anything below 2.5V. 1V is chosen for certain embodiments for
maximum compatibility with the various sensing elements. This keeps
the sensors 102 within the linear region, as well as reduces the
overall power consumption. 1V also provides a reasonable range of
measurement when used in conjunction with digital logic levels of
microcontroller circuitry.
[0061] In addition, the electrical current to each sensor 102 can
be limited to 1 mA to prevent damage to the sensing element 102. A
simple series resistor can be used as a cost-effective means of
limiting the current. This further protects the entire circuit or
system from a short circuit.
[0062] The SPST switches 1406 provide a means to individually
connect or disconnect sensors 102 to the voltage reference 1402.
This allows the system to dynamically control a subset of active
sensors 102, modulating the overall power consumption. If a sensor
102 falls below a certain resistance value, it can be disabled to
maintain current consumption below an acceptable limit.
Additionally, the same sensor chip 304 configuration can be used in
multiple applications, and only have a subset of the sensor
channels 102 selectively enabled. Furthermore, if a specific
channel 102 is identified to be non-functional or "broken" it can
be disconnected and ignored by the application.
[0063] FIG. 15 is a diagram illustrating an example measurement
circuit 1500 that can be included in the system of FIG. 4 in
accordance with one embodiment. The measurement circuit 1500, in
this example, consists of a multiplexer 1502, current mirror 1504,
a current to voltage stage 1506, and a gain stage 1508. The output
of the measurement circuit can be sent to the ADC 1510 within
element 404 of system 400. A separate measurement circuit which
isolates a single or set of sensing elements 102 allows for
minimizing cross-talk between the sensors 102. The sensors 102 of
interest are connected to their own reference voltage when being
measured, preventing transients on the parked sensors 102 from
affecting the supplied voltage or noise.
[0064] FIG. 16 is a diagram if an example multiplexer 1502
implementation in accordance with one embodiment. The multiplexer
1502 allows for selecting 1 of N channels 102. In certain
embodiments, the multiplexer 1502 can be implemented as SPST
switches. Combining multiple resistances in parallel can act as an
offset current to the sensor channel(s) 102 of interest. For
example, combining a 10 kOhm sensor with a 1 MOhm sensor yields a
0.101 mA current versus measuring the 1 MOhm sensor alone which
would provide 0.001 mA.
[0065] Take two sensing elements 102, which are used for the same
gas with one saturating at a lower concentration, causing the
resistance to plateau. If sensor element `1` reaches a plateau at
100 ppb, and sensor element `2` only starts showing response at 100
ppb and plateaus at 1000 ppb, these can both be simultaneously
connected and measured to cover the entirety of the range from 0
ppb to 1000 ppb. From 0-100 ppb, sensor `2` acts as an offset only
while sensor `1` shows a change in resistance. From 100 ppb to 1000
ppb sensor `1` acts as an offset only whereas sensor `2` shows a
change in resistance.
[0066] In the case of multiple channels 102, using an offset of 10
kOhm along with a 1 MOhm resistor can reduce the settling time if
switching from a sensor channel 102 with resistance value closer to
the smaller of the two. This allows the overall current to be on
the same order of magnitude, reducing the settling time.
[0067] The circuit can also act as a current adder for multiple
sensors 102, while at the same time cancelling out uncertainty and
noise. If multiple sensors 102 of 1 MOhm are connected, instead of
measuring the change of 0.001 mA it becomes a measurement of
N*0.001 mA. White noise introduced by the system can also be
cancelled out by averaging these signals providing a sqrt(N) factor
of improvement. This can also act as a means of speeding up
measurement time if there are multiple sensing elements 102 with
similar properties.
[0068] FIG. 17 is a diagram illustrating an example parking circuit
1400 and example measurement circuit 1500 coupled with a plurality
of sensors 102. The multiplexer circuit 1502 and the connection
with the parking circuit 1400 allows for a make-before-break
operation. A single channel 102 can be connected to both the
measurement 1500 and parking circuit 1400 simultaneously. The
sensor channel 102 is then disconnected from the parking circuit
1400 while connected to the measurement circuit 1500. As they are
both at the same voltage or potential, this allows for minimizing
the transient load on the sensor channel and the sensing element
102.
[0069] FIG. 18 is a diagram illustrating an OP-AMP circuit 1800
that can be used in place of the current mirror 1504 of FIG. 15.
The current mirror is one method of creating a constant voltage
source, but a similar circuit with an OP-AMP could be utilized. The
gain stage is implemented as a separate programmable gain amplifier
but can be integrated with the current mirror design if
desired.
[0070] An example of integrated gain could be a current mirror that
has different mirroring ratios, such as but not limited to 1:1,
1:2, 1:4, 1:8, and so on.
[0071] In this implementation of a current mirror, the voltage
applied to the sensing element 102 is also 1V, but again has the
same properties as the parking circuit 1400. It should be less than
2.5V and be current limited to prevent damage to the sensing
element 102.
[0072] FIG. 19 is a diagram illustrating a circuit for converting
the output of the current mirror 1504 into an analog signal that
can be sent to the ADC 1510. The output of the current mirror 1504
is connected to a resistor Rn to convert the current into a voltage
for measurement with an ADC 1510. There are 8 different resistors
(Rn) in resistor network 1902, connected to SPST switches (not
shown) on the output. Each resistor Rn of network 1902 can be
connected in parallel to increase the number of possible matching
resistors. A resistance that is the same value or larger than that
of the sensors 102 is ideal, allowing for the output voltage to be
at least 1V. The output resistor Rn in network 1902 is chosen to
maximize the voltage for measurement. Depending on the reference on
the ADC 1510 and the known resistance range of the sensors 102
various resistance values can be made.
[0073] The current across the sensor (Is) is the same as the
current into the mirror (Iin), which is calculated by the voltage
across the sensors (Vs) divided by the resistance of the sensor
(Rs): Iin=Is=Vs/Rs.
[0074] The current output is set by the current mirror gain ratio
(G1): Iout=G1*Vs/Rs.
[0075] The voltage desired at the input of the ADC 1510 is
dependent on the reference. The target threshold for the ADC 1510
is typically within 70% to 90% to maximize the signal while
allowing additional headroom for the sensor to change. Thus:
Vadc*ADCthreshold=Rvs*Iout or
Rvs=[(Vadc*ADCthreshold)/(G1*Vs)]*Rs.
[0076] For example, the sensor 102 has a voltage of 1V, the ADC
1510 has a 2.5V reference, and the current mirror 1504 provides a
1:1 ratio, then:
Rvs@70%=1.75*Rs and Rvs@90%=2.25*Rs.
[0077] In this example, there are 8 geometrically spaced resistors
(Rn) in network 1902 ranging from 17.8 kOhms to 5 MOhms but values
can be spaced asymmetrically if the sensing elements 102 are not
evenly spaced in terms of resistance values. This entire resistor
block can be replaced with a transimpedance amplifier (TIA) as an
alternative means of converting current to voltage.
[0078] Additionally, there is a secondary gain stage which consists
of an OP-AMP 1508 with 8 resistors (Rn) in network 1904 connected
to SPST switches (not shown). The same idea as with the initial
voltage select resistor, can be applied here for the gain. In some
implementations it may be ideal to have asymmetric spacing on the
current to voltage conversion, and symmetric spacing on the
secondary gain. One is specific to the resistance ranges of the
sensing elements 102, and one is generic for the overall gain. This
breaks the overall gain component, G into two components of G1 and
G2:
Rvs=[(Vadc*ADCthreshold)/(G1*G2*Vs)]*Rs
[0079] The purpose of gain here is to provide the maximum input
into the ADC 1510. In this case a 2.5V reference is used and the
circuit attempts to provide as close as possible to 2.5V, while
still maintaining enough room for changes in the sensing element's
resistance to avoid saturating the signal. A SAR ADC 1510 can be
used to allow for oversampling and reducing noise, and error stack
up in the preceding circuit stages.
[0080] Potential sources of error stack up that are introduced in
each sample, include but are not limited to the voltage reference
error, current mirror transfer from input to output, OP-AMP 1508
noise gain, thermal coupling, etc.
[0081] FIG. 5 shows the basic flow of information through a
complete nano gas sensor system, such as system 400 described in
more detail below. When the sensor array 305 is exposed to the
mixture of gas analytes 108 in its environment, in step 502, the
sensitive layers 104 of the materials deposited on the sensor
elements 102, or sensing channels react, according to their
formulation 202, to the presence of specific component gases in the
mixture. The reaction causes a change in the electrical
characteristics of the sensing channels 102, which is captured by
the transducer in the electronics sub-system, in step 504, and then
analyzed by the pattern recognition system programmed in the
sub-system MCU, in step 506. The output is an absolute value of the
concentration of the gases being detected. This is then combined,
in step 508, with other desirable meta-data such as time or
geo-location into a digital record. This digital record (or a
portion of it) can optionally be displayed locally in step 510 (for
example, in the case of a wearable application where the sensor is
paired to a phone, the data can be further manipulated and
displayed by a specially written mobile application running on the
phone). More importantly the data is uploaded, via a mechanism that
is dependent on the application, to a Cloud data platform in step
512, where the data can be normalized in step 514 and accessed via
various application in step 516.
[0082] The fourth element is a MCU-based data acquisition and
measurement engine, or digital backend, which also provides
additional functions such as overall sensor system management and
communication, as necessary with encryption, to and from a larger
system into which the sensor is embedded. The digital back end
consists of a microcontroller, integrated circuits, and data
acquisition optimization algorithms. The digital back-end acts as
the controller for the analog front-end. The biasing and the gain
settings for each channel are optimized by the digital back end.
This includes, but is not limited to power consumption, sampling
time, sampling period, and signal-to-noise ratio.
[0083] FIG. 20 is a diagram illustrating certain components of the
digital backend 406 in accordance with one embodiment. In certain
embodiments of the system 400, an additional temperature and
humidity sensor 2002 can be added, as well as other sensors such as
a barometer, UV and visible light sensor 2004, etc. These are
connected through digital interfaces such as I2C, SPI, UART, etc.,
to MCU 2000. The sensor data from array 305 is used as one of the
inputs to a pattern recognition algorithm as described herein.
[0084] The analog front end 404 provides a range of gain settings
to be controlled and stored by the digital back end 406. The
initial calibration step attempts to maximize the fill of the ADC
1510 between 70% to 90% of the analog reference. The fill values
can be changed depending on the integral non-linearity (INL) or
differential non-linearity (DNL) of the ADC 1510. This can be
either an iterative search, increasing the gain in a linear
fashion, a binary search through the range of gain settings, or a
direct calculation. Each sensor channel 102 goes through this
process and the selected gain settings are stored in memory. After
each measurement, the gain settings are updated for the next
cycle.
[0085] The measurement of the external sensors 2002-2006 are
synchronized with that of the nano gas sensors 102 to minimize the
phase delay. For example, if a humidity sensor takes 25 ms to make
a conversion and provide a result, the conversion will be started
25 ms before the nano gas sensors' measurement will be
completed.
[0086] As illustrated in FIG. 21, oversampling of the data can be
obtained by taking repeated ADC readings and averaging. This
oversampling rate is adjusted to minimize the latency between each
channel 102. Depending on the resistance range of the sensor
channel 102, the oversampling factor can be increased.
[0087] The order the channels 102 are sampled can be optimized to
reduce the data acquisition time. Sensors 102 can be measured in
either ascending or descending order, by voltage or resistance.
This minimizes the delta between successive channels, thereby
reducing the settling time required between each channel as
illustrated in the graph of FIG. 22.
[0088] The digital system also disables sensor channels 102 that
are not of interest. This includes channels 102 that are determined
to be outliers, damaged or otherwise non-responsive. Outliers are
determined based on the expected resistance range of sensor
channels 102. Additionally, if a sensor chip 304 contains multiple
channels 102 of the same material, deviations from the average
response curve can be used to identify outliers.
[0089] Damaged sensors 102 may be either a short or an open
circuit. In either case the resistance is either too low or too
high and can be disconnected from the circuit and ignored when
iterating through the channels 102. The cutoff threshold for large
resistances depends on the lower detection limit (LDL) of the
application, the sensitivity of the sensing element 102, and the
effective resolution of the ADC 1510. If the sensitivity of a
sensing element 102 is known to be a certain percentage per ppb of
gas, the threshold can be calculated with the following, where SnR
is the desired signal-to-noise ratio.
[Vbias/(LDL*Rsensitivity)]*Gain>SnR*[(ADCresolution)/Varef]
[0090] As illustrated in FIG. 23 the sampling rate can be
dynamically modulated depending on the detection time and
application. Dynamic modulation allows for reducing the duty cycle
of the digital back-end 406, reducing overall power consumption. In
situations where the gas concentration is not expected to rapidly
change, sampling rate can be reduced. Additionally, depending on
the desired response time of the sensor the sampling rate may be
decreased or increased.
[0091] For any given application, the sampling rate does not have
to be constant. It can be increased as a change in the sensors
electrical properties are being detected. For example, there can be
a detection period where the sampling rate is relatively slow, at 1
sample per second. As the resistance changes exceeds a given
threshold, this can be increased to 5 samples per second.
[0092] The third and fourth elements are designed to work together
and to form a complete electronic sub-system specifically tuned to
work with the array of sensing channels 305 implemented as a
separate component. The transducer 404 is firmware configurable to
provide optimal A/D conversion for a pattern recognition system
running on the MCU 406 and implementing the gas detection and
measurement algorithm(s).
[0093] The electronic sub-system 402 is suitable for implementation
in a variety of technologies depending on target use model and
technical/cost trade-offs. PCB implementations will enable quick
turn-around and the declination of a family of related products
(for instance with different communication interfaces) to support
multiple form factors and applications with the same core
electronics. When size and power/performance trade-offs are
critical, the electronic sub-system 402 is implemented as a System
On a Chip (SoC), which can then be integrated together with a MEMS
chip carrying the array of sensing channels 305 into a System In a
Package (SIP).
[0094] The sensor die 304 must then be assembled with the sensor's
electronic sub-system to complete the hybrid nanostructure gas
sensor 400 for which a functional block diagram is shown in FIG.
4.
[0095] The electronic sub-system can be implemented as a PCB or as
a SoC. If the PCB route is followed the sensor die 304 can be
either wire-bonded to the electronic sub-system 402 board after
completion of the PCB Assembly (PCBA) step or, if the sensor die
304 has itself been individually assembled in a SMT package, it can
be soldered on the board as part of PCBA. If the SoC route is
followed, the sensor die together with the SoC die of the
electronic sub-system 402 can be stacked and assembled together
into a single package (System In a Package) or each can possibly be
assembled into individual packages.
[0096] Either assembled into its own package or assembled into a
SIP, the sensor chip 304 must be exposed to ambient air. Therefore,
the package lid must include a hole of sufficient size over the
sensor.
[0097] Testing happens at various points of the sensor
manufacturing process.
[0098] After sensor functionalization (deposition of the molecular
formulations 204), certain handling precautions must be followed
for the rest of the product manufacturing flow to prevent
accidental damage to the sensor chip 304 (e.g. a pick and place
tool must not make contact with the surface of the sensing
elements).
[0099] The fifth element is the gas detection and measurement
algorithm. The algorithm implements a method for predicting target
gas concentration by reading the hybrid nanostructure sensor
array's multivariate output and processing it inside the algorithm.
The algorithm analyzes sensor signals in real time and outputs
estimated values for concentrations of target gases. The algorithm
development is based on models that are specific to the materials
deposited on the sensing channels of the sensor array. These models
are trained based on the collection of an abundant volume of data
in the laboratory (multiple concentrations of target gases,
combinations of gases, various values of temperature, relative
humidity and other environmental parameters). Sophisticated
supervised modeling techniques are used to attain the best possible
agreement between true and predicted values of target gas
concentrations. Prior to deployment, extensive lab and field
testing is carried out to optimize model performance and finalize
sensor validation.
[0100] The first five elements together constitute the hybrid
nanostructure gas sensor 400 and provide all the functionality
necessary to detect multiple gases 108 in ambient air at the same
time and to report their absolute concentrations. The sensing
capability of the hybrid nanostructure sensor array 305 is always
"on" and the gas detection and measurement algorithm makes it
possible for the sensor 400 to require no special calibration step
before use and to remain self-calibrating through its operational
life.
[0101] The sixth element is the Cloud Data Platform that enables a
virtually unlimited number of sensors 400 deployed as part of a
virtually unlimited number of applications to be hosted in a global
database where big data techniques can be used to analyze, query
and visualize the information to infer actionable insight. The use
of a Cloud-based environment provides all the necessary flexibility
to customize how the data can be partitioned, organized, protected
and accessed based on the rights of individual tenants.
[0102] The Cloud data platform provides another layer of
sophistication to the system by allowing Cloud applications to
operate on the data set. For instance, sensors 400 that are located
in the same vicinity would typically report consistent gas values
thus allowing errant results to be identified and a possible
malfunction of one node of a network of sensors investigated.
[0103] The continuous collection of highly granular gas information
by a multitude of connected devices (IoT--Internet Of Things) is
critical to go beyond monitoring to generate actionable insight
from large amount of collected data (Big Data Analytics, Artificial
Intelligence).
[0104] A few application examples are highlighted below.
Example 1
[0105] We take 20,000 breaths every day and the air we breathe
impacts our health--the science is already clear on this--but we
rarely know what is in the air we breathe. To take meaningful
action, consumers, scientists, public officials and business owners
need the ability to measure air pollution at a personal, local and
granular level which has, before this invention, been impossible
due to the limitations of commercially available gas sensors
mentioned above.
[0106] Mounting evidence suggests that prenatal and early life
exposure to common environmental toxins, such as air pollution from
fossil fuels, can cause lasting damage to the developing human
brain. These effects are especially pronounced in highly vulnerable
fetuses, babies, and toddlers as most of the brain's structural and
functional architecture is established during these early
developmental periods. These disruptions to healthy brain
development can cause various cognitive, emotional, and behavioral
problems in later infancy and childhood.
[0107] The sensor technology described herein allows researchers to
gather highly detailed, accurate data about pregnant women's
exposure to environmental air pollution and the resulting effects
on the developing brain. The availability of this technology will
represent a profound advance on current methods and efforts in the
field that will have far-reaching consequences for improving
newborn and child health throughout the world.
[0108] More generally, personal air monitoring and local indoor and
outdoor monitoring will be a breakthrough for scientific research,
healthcare interventions, personal preventive actions, advocacy and
more.
[0109] The sensor technology described herein can deliver complete
processing and gas results to a broad spectrum of smart systems
under development for the Smart Cities of tomorrow. The sensor is
designed for Plug and Play integration into IoT devices and the
small form factor is compatible with a multitude of devices from
LED lights to smart meters, to standalone monitoring stations, to
non-stationary devices (drones, public vehicles, wearables, phones,
etc.).
Example 2
[0110] The sensor technology described herein can be used in smart
appliances such as connected refrigerators, that will help
customers monitor food freshness, detect spoilage and the presence
of harmful pesticide residues. The simultaneous, multi-gas, sensing
capability of the invention will enable sensors that can recognize
the gas patterns associated with the condition of specific
foods.
Example 3
[0111] A network or grid of the sensors 400 described herein, can
be integrated into industrial areas such as petrochemical complexes
and oil refineries to allow companies to monitor the sites during
regular operation (e.g. for leaks) or in the event of natural or
human-made disasters. The sensors can also be installed in drones
for data collection in hard to reach or potentially dangerous area.
The ability of the technology to be deployed in wearables and in
fixed and mobile networks will provide both personal protection and
granular data across large area, allow the constant monitoring of a
facility for preventive measures to be taken in a timely fashion,
save critical time when urgent decision making is required and
provide invaluable information to protect workers and emergency
personnel.
[0112] The same technology can place powerful new tools in the
hands of first responders and officials responsible for public
safety and homeland security.
[0113] FIG. 6 shows an example product 600, in this case a
battery-powered wearable device, with the sensor 400 implemented as
a small PCB. The sensor technology lends itself to integration into
any number of IoT devices. While the sensor does not need the
active creation of an airflow to function, the sensitive layers 104
at the surface of the sensor must be exposed to ambient air and at
the same time provided a reasonable amount of protection from dust
and fluids. This is usually achieved by designing an air interface
that ensures that the sensor 400 is behind a perforated shield
(e.g. the lid of an enclosure) with a thin membrane (PTFE, 0.5 um
mesh) being used to provide splash and dust protection. Outdoor
applications may require the design of a more complicated air
interface to meet the weather-proofing requirements.
[0114] FIG. 7 is a block diagram illustrating an example wired or
wireless system 550 that can be used in connection with various
embodiments described herein. For example the system 550 can be
used as or in conjunction with one or more of the platforms,
devices or processes described above, and may represent components
of a device, such as sensor 400, the corresponding backend or cloud
server(s), and/or other devices described herein. The system 550
can be a server or any conventional personal computer, or any other
processor-enabled device that is capable of wired or wireless data
communication. Other computer systems and/or architectures may be
also used, as will be clear to those skilled in the art.
[0115] The system 550 preferably includes one or more processors,
such as processor 560. Additional processors may be provided, such
as an auxiliary processor to manage input/output, an auxiliary
processor to perform floating point mathematical operations, a
special-purpose microprocessor having an architecture suitable for
fast execution of signal processing algorithms (e.g., digital
signal processor), a slave processor subordinate to the main
processing system (e.g., back-end processor), an additional
microprocessor or controller for dual or multiple processor
systems, or a coprocessor. Such auxiliary processors may be
discrete processors or may be integrated with the processor 560.
Examples of processors which may be used with system 550 include,
without limitation, the Pentium.RTM. processor, Core i7.RTM.
processor, and Xeon.RTM. processor, all of which are available from
Intel Corporation of Santa Clara, Calif. Example processor that can
be used in system 400 include the ARM family of processors and the
new open source RISC V processor architecture.
[0116] The processor 560 is preferably connected to a communication
bus 555. The communication bus 555 may include a data channel for
facilitating information transfer between storage and other
peripheral components of the system 550. The communication bus 555
further may provide a set of signals used for communication with
the processor 560, including a data bus, address bus, and control
bus (not shown). The communication bus 555 may comprise any
standard or non-standard bus architecture such as, for example, bus
architectures compliant with industry standard architecture (ISA),
extended industry standard architecture (EISA), Micro Channel
Architecture (MCA), peripheral component interconnect (PCI) local
bus, or standards promulgated by the Institute of Electrical and
Electronics Engineers (IEEE) including IEEE 488 general-purpose
interface bus (GPIB), IEEE 696/S-100, and the like.
[0117] System 550 preferably includes a main memory 565 and may
also include a secondary memory 570. The main memory 565 provides
storage of instructions and data for programs executing on the
processor 560, such as one or more of the functions and/or modules
discussed above. It should be understood that programs stored in
the memory and executed by processor 560 may be written and/or
compiled according to any suitable language, including without
limitation C/C++, Java, JavaScript, Pearl, Visual Basic, .NET, and
the like. The main memory 565 is typically semiconductor-based
memory such as dynamic random access memory (DRAM) and/or static
random access memory (SRAM). Other semiconductor-based memory types
include, for example, synchronous dynamic random access memory
(SDRAM), Rambus dynamic random access memory (RDRAM), ferroelectric
random access memory (FRAM), and the like, including read only
memory (ROM).
[0118] The secondary memory 570 may optionally include an internal
memory 575 and/or a removable medium 580, for example a floppy disk
drive, a magnetic tape drive, a compact disc (CD) drive, a digital
versatile disc (DVD) drive, other optical drive, a flash memory
drive, etc. The removable medium 580 is read from and/or written to
in a well-known manner. Removable storage medium 580 may be, for
example, a floppy disk, magnetic tape, CD, DVD, SD card, etc.
[0119] The removable storage medium 580 is a non-transitory
computer-readable medium having stored thereon computer executable
code (i.e., software) and/or data. The computer software or data
stored on the removable storage medium 580 is read into the system
550 for execution by the processor 560.
[0120] In alternative embodiments, secondary memory 570 may include
other similar means for allowing computer programs or other data or
instructions to be loaded into the system 550. Such means may
include, for example, an external storage medium 595 and an
interface 590. Examples of external storage medium 595 may include
an external hard disk drive or an external optical drive, or and
external magneto-optical drive.
[0121] Other examples of secondary memory 570 may include
semiconductor-based memory such as programmable read-only memory
(PROM), erasable programmable read-only memory (EPROM),
electrically erasable read-only memory (EEPROM), or flash memory
(block oriented memory similar to EEPROM). Also included are any
other removable storage media 580 and communication interface 590,
which allow software and data to be transferred from an external
medium 595 to the system 550.
[0122] System 550 may include a communication interface 590. The
communication interface 590 allows software and data to be
transferred between system 550 and external devices (e.g.
printers), networks, or information sources. For example, computer
software or executable code may be transferred to system 550 from a
network server via communication interface 590. Examples of
communication interface 590 include a built-in network adapter,
network interface card (NIC), Personal Computer Memory Card
International Association (PCMCIA) network card, card bus network
adapter, wireless network adapter, Universal Serial Bus (USB)
network adapter, modem, a network interface card (NIC), a wireless
data card, a communications port, an infrared interface, an IEEE
1394 fire-wire, or any other device capable of interfacing system
550 with a network or another computing device.
[0123] Communication interface 590 preferably implements industry
promulgated protocol standards, such as Ethernet IEEE 802
standards, Fiber Channel, digital subscriber line (DSL),
asynchronous digital subscriber line (ADSL), frame relay,
asynchronous transfer mode (ATM), integrated digital services
network (ISDN), personal communications services (PCS),
transmission control protocol/Internet protocol (TCP/IP), serial
line Internet protocol/point to point protocol (SLIP/PPP), and so
on, but may also implement customized or non-standard interface
protocols as well.
[0124] Software and data transferred via communication interface
590 are generally in the form of electrical communication signals
605. These signals 605 are preferably provided to communication
interface 590 via a communication channel 600. In one embodiment,
the communication channel 600 may be a wired or wireless network,
or any variety of other communication links. Communication channel
600 carries signals 605 and can be implemented using a variety of
wired or wireless communication means including wire or cable,
fiber optics, conventional phone line, cellular phone link,
wireless data communication link, radio frequency ("RF") link, or
infrared link, just to name a few.
[0125] Computer executable code (i.e., computer programs or
software) is stored in the main memory 565 and/or the secondary
memory 570. Computer programs can also be received via
communication interface 590 and stored in the main memory 565
and/or the secondary memory 570. Such computer programs, when
executed, enable the system 550 to perform the various functions of
the present invention as previously described.
[0126] In this description, the term "computer readable medium" is
used to refer to any non-transitory computer readable storage media
used to provide computer executable code (e.g., software and
computer programs) to the system 550. Examples of these media
include main memory 565, secondary memory 570 (including internal
memory 575, removable medium 580, and external storage medium 595),
and any peripheral device communicatively coupled with
communication interface 590 (including a network information server
or other network device). These non-transitory computer readable
mediums are means for providing executable code, programming
instructions, and software to the system 550.
[0127] In an embodiment that is implemented using software, the
software may be stored on a computer readable medium and loaded
into the system 550 by way of removable medium 580, I/O interface
585, or communication interface 590. In such an embodiment, the
software is loaded into the system 550 in the form of electrical
communication signals 605. The software, when executed by the
processor 560, preferably causes the processor 560 to perform the
inventive features and functions previously described herein.
[0128] In an embodiment, I/O interface 585 provides an interface
between one or more components of system 550 and one or more input
and/or output devices. Example input devices include, without
limitation, keyboards, touch screens or other touch-sensitive
devices, biometric sensing devices, computer mice, trackballs,
pen-based pointing devices, and the like. Examples of output
devices include, without limitation, cathode ray tubes (CRTs),
plasma displays, light-emitting diode (LED) displays, liquid
crystal displays (LCDs), printers, vacuum florescent displays
(VFDs), surface-conduction electron-emitter displays (SEDs), field
emission displays (FEDs), and the like.
[0129] The system 550 also includes optional wireless communication
components that facilitate wireless communication over a voice and
over a data network. The wireless communication components comprise
an antenna system 610, a radio system 615 and a baseband system
620. In the system 550, radio frequency (RF) signals are
transmitted and received over the air by the antenna system 610
under the management of the radio system 615.
[0130] In one embodiment, the antenna system 610 may comprise one
or more antennae and one or more multiplexors (not shown) that
perform a switching function to provide the antenna system 610 with
transmit and receive signal paths. In the receive path, received RF
signals can be coupled from a multiplexor to a low noise amplifier
(not shown) that amplifies the received RF signal and sends the
amplified signal to the radio system 615.
[0131] In alternative embodiments, the radio system 615 may
comprise one or more radios that are configured to communicate over
various frequencies. In one embodiment, the radio system 615 may
combine a demodulator (not shown) and modulator (not shown) in one
integrated circuit (IC). The demodulator and modulator can also be
separate components. In the incoming path, the demodulator strips
away the RF carrier signal leaving a baseband receive audio signal,
which is sent from the radio system 615 to the baseband system
620.
[0132] If the received signal contains audio information, then
baseband system 620 decodes the signal and converts it to an analog
signal. Then the signal is amplified and sent to a speaker. The
baseband system 620 also receives analog audio signals from a
microphone. These analog audio signals are converted to digital
signals and encoded by the baseband system 620. The baseband system
620 also codes the digital signals for transmission and generates a
baseband transmit audio signal that is routed to the modulator
portion of the radio system 615. The modulator mixes the baseband
transmit audio signal with an RF carrier signal generating an RF
transmit signal that is routed to the antenna system and may pass
through a power amplifier (not shown). The power amplifier
amplifies the RF transmit signal and routes it to the antenna
system 610 where the signal is switched to the antenna port for
transmission.
[0133] The baseband system 620 is also communicatively coupled with
the processor 560. The central processing unit 560 has access to
data storage areas 565 and 570. The central processing unit 560 is
preferably configured to execute instructions (i.e., computer
programs or software) that can be stored in the memory 565 or the
secondary memory 570. Computer programs can also be received from
the baseband processor 610 and stored in the data storage area 565
or in secondary memory 570, or executed upon receipt. Such computer
programs, when executed, enable the system 550 to perform the
various functions of the present invention as previously described.
For example, data storage areas 565 may include various software
modules (not shown).
[0134] Various embodiments may also be implemented primarily in
hardware using, for example, components such as application
specific integrated circuits (ASICs), or field programmable gate
arrays (FPGAs). Implementation of a hardware state machine capable
of performing the functions described herein will also be apparent
to those skilled in the relevant art. Various embodiments may also
be implemented using a combination of both hardware and
software.
[0135] Furthermore, those of skill in the art will appreciate that
the various illustrative logical blocks, modules, circuits, and
method steps described in connection with the above described
figures and the embodiments disclosed herein can often be
implemented as electronic hardware, computer software, or
combinations of both. To clearly illustrate this interchangeability
of hardware and software, various illustrative components, blocks,
modules, circuits, and steps have been described above generally in
terms of their functionality. Whether such functionality is
implemented as hardware or software depends upon the particular
application and design constraints imposed on the overall system.
Skilled persons can implement the described functionality in
varying ways for each particular application, but such
implementation decisions should not be interpreted as causing a
departure from the scope of the invention. In addition, the
grouping of functions within a module, block, circuit or step is
for ease of description. Specific functions or steps can be moved
from one module, block or circuit to another without departing from
the invention.
[0136] Moreover, the various illustrative logical blocks, modules,
functions, and methods described in connection with the embodiments
disclosed herein can be implemented or performed with a general
purpose processor, a digital signal processor (DSP), an ASIC, FPGA
or other programmable logic device, discrete gate or transistor
logic, discrete hardware components, or any combination thereof
designed to perform the functions described herein. A
general-purpose processor can be a microprocessor, but in the
alternative, the processor can be any processor, controller,
microcontroller, or state machine. A processor can also be
implemented as a combination of computing devices, for example, a
combination of a DSP and a microprocessor, a plurality of
microprocessors, one or more microprocessors in conjunction with a
DSP core, or any other such configuration.
[0137] Additionally, the steps of a method or algorithm described
in connection with the embodiments disclosed herein can be embodied
directly in hardware, in a software module executed by a processor,
or in a combination of the two. A software module can reside in RAM
memory, flash memory, ROM memory, EPROM memory, EEPROM memory,
registers, hard disk, a removable disk, a CD-ROM, or any other form
of storage medium including a network storage medium. An exemplary
storage medium can be coupled to the processor such the processor
can read information from, and write information to, the storage
medium. In the alternative, the storage medium can be integral to
the processor. The processor and the storage medium can also reside
in an ASIC.
[0138] Any of the software components described herein may take a
variety of forms. For example, a component may be a stand-alone
software package, or it may be a software package incorporated as a
"tool" in a larger software product. It may be downloadable from a
network, for example, a website, as a stand-alone product or as an
add-in package for installation in an existing software
application. It may also be available as a client-server software
application, as a web-enabled software application, and/or as a
mobile application.
[0139] While certain embodiments have been described above, it will
be understood that the embodiments described are by way of example
only. Accordingly, the systems and methods described herein should
not be limited based on the described embodiments. Rather, the
systems and methods described herein should only be limited in
light of the claims that follow when taken in conjunction with the
above description and accompanying drawings.
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